Suspicious Behavior Detection System for an Open Space Parking Based on Recognition of Human Elemental Actions

Abstract

Studies for video surveillance applications for preventing various crimes such as stealing and violence have become a hot topic. This paper proposes a new video surveillance system that can detect suspicious behaviors such as a car break-in and vandalization in an open space parking, and that is based on image processing. The proposed system has the following features: it 1)deals time series data flow, 2)recognizes “human elemental actions” using statistic features, and 3)detects suspicious behavior using Subspace method and AdaBoost. We conducted the experiments to test the performance of the proposed system using open space parking scenes. As a result, we obtained about 10.0% for false positive rate, and about 4.6% for false negative rate.